Check Type Annotations for transforms/functional_pil and transforms/functional_tensor
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- Dominant language
- Python
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Description
🚀 Feature
As spotted in https://github.com/pytorch/vision/pull/4234#pullrequestreview-731356320
There are some minor cases where type annotations do not match.
We should probably rectify them and ensure that the types annotations match.
P.S.
But I'm willing to leave for any new contributor! Otherwise I will complete it in the next week
cc @vfdev-5 @datumbox @pmeier I think this can be a good first issue for people awaiting to contribute 😄
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the type-annotation mismatches identified in the review of pull request #4234, then inspect transforms/functional_pil and transforms/functional_tensor. Compare the annotations with the existing function behavior in both modules; done means the annotations consistently match what those functions accept and return.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision
- Issue type
- Feature
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 42/100